What you don’t know about working with AWS
You’ll get further by understanding what a company values and what makes its employees tick.
You’ll get further by understanding what a company values and what makes its employees tick.
Taking a great open source project and building it into a product people will pay for requires skills in development and operations.
Database popularity rises and falls over decades, not years. The databases that developers are interested in trying today may permeate the enterprises of the future.
Data scientist may be one of the sexiest jobs of our century, as Harvard Business Review opines, but it sure does involve a lot of unsexy, manual labour.
AI-driven software development is great. But don’t lose sight of all the things it can’t do yet.
Despite the hype, especially around self-driving cars, AI is writing code, designing Google chip floor plans, and telling us how much to trust it.
HPC projects require massive quantities of compute resources. Pairing simulation and specialised hardware with the cloud powers future breakthroughs,
Investment in open source technologies and companies has been going strong for more than two decades.
Moving workloads in and out of the cloud isn’t really possible—or a good idea.
If the ubiquitous spreadsheet program is the gateway to data science, Python aims to be the next step.
Making great efforts to tout its closed source software, Snowflake may be trying to convince an audience that doesn't really care.
Try using Kubernetes like an app server for smaller teams instead of treating it like a centralised cloud.
Both the single-stack architecture and the best-of-breed approaches can limit you. Open source and building in the capability for change are key.
Companies that jumped in early are reaping the rewards, but it’s not too late. Businesses must now find the people and partners to help move ahead.
Commodity services that would allow workloads to run across multiple clouds don’t exist. But that hasn’t stopped the multi-clouders from trying.
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